Are Correlates of Physical Activity in Adolescents Similar Across Ethnicity/Race and Sex: Implications for Interventions

in Journal of Physical Activity and Health

Click name to view affiliation

Jonathan M. Miller
Search for other papers by Jonathan M. Miller in
Current site
Google Scholar
PubMed Close
,
Mark A. Pereira
Search for other papers by Mark A. Pereira in
Current site
Google Scholar
PubMed Close
,
Julian Wolfson
Search for other papers by Julian Wolfson in
Current site
Google Scholar
PubMed Close
,
Melissa N. Laska
Search for other papers by Melissa N. Laska in
Current site
Google Scholar
PubMed Close
,
Toben F. Nelson
Search for other papers by Toben F. Nelson in
Current site
Google Scholar
PubMed Close
, and
Dianne Neumark-Sztainer
Search for other papers by Dianne Neumark-Sztainer in
Current site
Google Scholar
PubMed Close
DOI:
https://doi.org/10.1123/jpah.2018-0600
Keywords:
MVPA; health disparities; epidemiology; health determinants
In Print:
Volume 16: Issue 12
Page Range:
1163–1174
Restricted access

Background: This study tested for differences in personal, social, and environmental correlates of moderate to vigorous physical activity (MVPA) across ethnicity/race in male and female adolescents. Methods: Self-reported MVPA and 47 potential correlates of MVPA were measured in an ethnically/racially diverse cross-sectional sample of adolescents, in Minnesota, who participated in EAT-2010 (Eating and Activity in Teens). Interactions of potential correlates with ethnicity/race on MVPA were tested in linear hierarchical regression models in boys and girls. Results: Boys reported 1.7 more weekly hours of MVPA than girls. White adolescents reported 1.1 to 2.1 more weekly hours of MVPA than nonwhite adolescents. Among girls, neighborhood road connectivity was negatively correlated with MVPA among Hispanic and Asian participants. Among boys, sports participation was positively correlated with MVPA among all ethnicities/races, except Asians. Home media equipment was positively correlated with MVPA among Hispanic boys, but negatively correlated among white boys. Conclusions: A few correlates of physical activity among adolescents differed intersectionally by ethnicity/race and sex. Sports participation and home media equipment may have differing impacts on physical activity across ethnicities and races in boys, whereas neighborhood features like road connectivity may have differing impacts on physical activity across ethnicities and races in girls.

Miller is with the Division of Family Medicine and Community Health, University of Minnesota, Minneapolis MN. Pereira, Laska, Nelson, and Neumark-Sztainer are with the Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN. Wolfson is with the Division of Biostatistics, University of Minnesota, Minneapolis, MN.

Miller (mill5687@umn.edu) is corresponding author.
  • Collapse
  • Expand

Journal of Physical Activity and Health

Cover Journal of Physical Activity and Health
  • 1.

    Dixon JB. The effect of obesity on health outcomes. Mol Cell Endocrinol. 2010;316(2):104–108. PubMed ID: 19628019 doi:10.1016/j.mce.2009.07.008

  • 2.

    Troiano RP, Berrigan D, Dodd KW, Mâsse LC, Tilert T, Mcdowell M. Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008;40(1):181–188. PubMed ID: 18091006 doi:10.1249/mss.0b013e31815a51b3

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 3.

    Sallis JF, Prochaska JJ, Taylor WC. A review of correlates of physical activity of children and adolescents. Med Sci Sports Exerc. 2000;32(5):963–975. PubMed ID: 10795788 doi:10.1097/00005768-200005000-00014

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4.

    Biddle SJH, Whitehead SH, O’Donovan TM, Nevill ME. Correlates of participation in physical activity for adolescent girls: a systematic review of recent literature. J Phys Act Health. 2005;2(4):423–434. doi:10.1123/jpah.2.4.423

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Uijtdewilligen L, Nauta J, Singh AS, et al. Determinants of physical activity and sedentary behaviour in young people: a review and quality synthesis of prospective studies. Br J Sports Med. 2011;45(11):896–905. PubMed ID: 21836173 doi:10.1136/bjsports-2011-090197

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 6.

    Sallis JF, Owen N. Ecological models of health behavior. In: Glanz K, Rimer B, Viswanath K, eds. Health Behavior: Theory Research and Practice. 5th ed. San Francisco, CA: Jossey-Bass; 2015:43–64.

    • Search Google Scholar
    • Export Citation
  • 7.

    Sagatun A, Kolle E, Anderssen SA, Thoresen M, Sogaard AJ. Three-year follow-up of physical activity in Norwegian youth from two ethnic groups: associations with socio-demographic factors. BMC Public Health. 2008;8:419. PubMed ID: 19102770 doi:10.1186/1471-2458-8-419

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8.

    Taverno Ross SE, Larson N, Graham DJ, Neumark-Sztainer D. Longitudinal changes in physical activity and sedentary behavior from adolescence to adulthood: comparing U.S.-born and foreign-born populations. J Phys Act Health. 2014;11(3):519–527. PubMed ID: 23416986 doi:10.1123/jpah.2011-0359

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 9.

    Winnail SD, Valois RF, McKeown RE, et al. Relationship between physical activity level and cigarette, smokeless tobacco, and marijuana use among public high school adolescents. J Sch Health. 1995;65(10):438–442. PubMed ID: 8789710 doi:10.1111/j.1746-1561.1995.tb08209.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 10.

    Myers L, Strikmiller PK, Webber LS, Berenson GS. Physical and sedentary activity in school children grades 5–8: the Bogalusa Heart Study. Med Sci Sports Exerc. 1996;28(7):852–859. PubMed ID: 8832539 doi:10.1097/00005768-199607000-00012

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11.

    Booth ML, Okely AD, Chey T, Bauman AE, Macaskill P. Epidemiology of physical activity participation among New South Wales school students. Aust N Z J Public Health. 2002;26(4):371–374. PubMed ID: 12233960 doi:10.1111/j.1467-842X.2002.tb00189.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12.

    Lowry R, Wechsler H, Galuska DA, Fulton JE, Kann L. Television viewing and its association with overweight, sedentary lifestyle, and insufficient consumption of fruits and vegetables among US high school students: differences by race, ethnicity and gender. J Sch Health. 2002;72(10):413–421. PubMed ID: 12617028 doi:10.1111/j.1746-1561.2002.tb03551.x

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    McGuire MT, Hannan PJ, Neumark-Sztainer D, et al. Parental correlates of physical activity in a racially/ethnically diverse adolescent sample. J Adolesc Heal. 2002;30(4):253–261. doi:10.1016/S1054-139X(01)00392-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    McGuire M, Neumark-Sztainer D, Story M. Correlates of time spent in physical activity and television watching in a multi-racial sample of adolescents. Pediatr Exerc Sci. 2002;14(41):75–86. doi:10.1123/pes.14.1.75

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 15.

    Wardle J, Jarvis MJ, Steggles N, et al. Socioeconomic disparities in cancer-risk behaviors in adolescence: baseline results from the Health and Behaviour in Teenagers Study (HABITS). Prev Med. 2003;36(6):721–730. doi:10.1016/S0091-7435(03)00047-1

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Kitzman-Ulrich H, Wilson DK, Van Horn ML, Lawman HG. Relationship of body mass index and psychosocial factors on physical activity in underserved adolescent boys and girls. Health Psychol. 2010;29(5):506–513. PubMed ID: 20836605 doi:10.1037/a0020853

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Taliaferro LA, Rienzo BA, Donovan KA, et al. Relationships between youth sport participation and selected health risk behaviors from 1999 to 2007. J Sch Health. 2010;80(8):399–410. PubMed ID: 20618623 doi:10.1111/j.1746-1561.2010.00520.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Springer AE, Lewis K, Kelder SH, Fernandez ME, Barroso CS, Hoelscher DM. Physical activity participation by parental language use in 4th, 8th, and 11th grade students in Texas, USA. J Immigr Minor Health. 2010;12(5):769–780. PubMed ID: 19365728 doi:10.1007/s10903-009-9249-4

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Ridgers ND, Saint-Maurice PF, Welk GJ, Siahpush M, Huberty J. Differences in physical activity during school recess. J Sch Health. 2011;81(9):545–551. PubMed ID: 21831067 doi:10.1111/j.1746-1561.2011.00625.x

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Kelly S, Melnyk BM, Belyea M. Predicting physical activity and fruit and vegetable intake in adolescents: a test of the information, motivation, behavioral skills model. Res Nurs Health. 2012;35(2):146–163. PubMed ID: 22262049 doi:10.1002/nur.21462

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Rosario M, Corliss HL, Everett BG, et al. Sexual orientation disparities in cancer-related risk behaviors of tobacco, alcohol, sexual behaviors, and diet and physical activity: pooled youth risk behavior surveys. Am J Public Health. 2014;104(2):245–254. PubMed ID: 24328632 doi:10.2105/AJPH.2013.301506

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 22.

    Graham DJ, Wall MM, Larson N, Neumark-Sztainer D. Multicontextual correlates of adolescent leisure-time physical activity. Am J Prev Med. 2014;46(6):605–616. PubMed ID: 24842737 doi:10.1016/j.amepre.2014.01.009

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Larson N, MacLehose R, Fulkerson JA, Berge JM, Story M, Neumark-Sztainer D. Eating breakfast and dinner together as a family: associations with sociodemographic characteristics and implications for diet quality and weight status. J Acad Nutr Diet. 2013;113(12):1601–1609. PubMed ID: 24139290 doi:10.1016/j.jand.2013.08.011

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 24.

    Neumark-Sztainer D, MacLehose R, Loth K, Fulkerson JA, Eisenberg ME, Berge J. What’s for dinner? Types of food served at family dinner differ across parent and family characteristics. Public Health Nutr. 2012;17(1):145–155. PubMed ID: 23083836 doi:10.1017/S1368980012004594

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 25.

    MetroGIS DataFinder. 2012. https://gisdata.mn.gov/. Accessed April 17, 2012.

  • 26.

    ESRI Business Analyst Desktop. 2012. http://www.esri.com/software/arcgis/extensions/businessanalyst/. Accessed April 17, 2012.

  • 27.

    Forsyth A, Larson N, Lytle L, et al. 2010. LEAN-GIS Protocols: Local Environment for Activity and Nutrition—Geographic Information Systems. Version 2.0. http://designforhealth.net/wp-content/uploads/2012/12/LEAN_Protocol_V2_120410.pdf. Accessed April 29, 2016.

    • Search Google Scholar
    • Export Citation
  • 28.

    D’sousa E, Forsyth A, Koepp J, et al. 2012. NEAT-GIS Protocols: Neighborhood Environment for Active Transport—Geographic Information Systems. http://www.designforhealth.net/pdfs/NEAT_GIS_V5_1_Jan2012.pdf. Accessed June 5, 2012.

    • Search Google Scholar
    • Export Citation
  • 29.

    Godin G, Shephard RJ. A simple method to assess exercise behavior in the community. Can J Appl Sport Sci. 1985;10(3):141–146. PubMed ID: 4053261

  • 30.

    Sirard JR, Hannan P, Cutler GJ, Nuemark-Sztainer D. Evaluation of 2 self-report measures of physical activity with accelerometry in young adults. J Phys Act Health. 2013;10(1):85–96. PubMed ID: 22241145 doi:10.1123/jpah.10.1.85

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Butland B, Jebb S, Kopelman P, et al. Tackling Obesities: Future Choices—Project Report. 2nd ed. London, UK: Government Office for Science; 2007.

    • Search Google Scholar
    • Export Citation
  • 32.

    Wang B, York N, Fang Y. Combining Type-III Analyses from Multiple Imputations. Paper presented at: SAS Global Forum Proceedings; 2014. http://support.sas.com/resources/papers/proceedings14/1543-2014.pdf.

    • Search Google Scholar
    • Export Citation
  • 33.

    Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol. 1995;57(1):289–300.

    • Search Google Scholar
    • Export Citation
  • 34.

    Barr-Anderson DJ, Flynn JI, Dowda M, et al. The modifying effects of race/ethnicity and socioeconomic status on the change in physical activity from elementary to middle school. J Adolesc Heal. 2017;61(5):562–570. doi:10.1016/j.jadohealth.2017.05.007

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 35.

    Pham KL, Harrison GG, Kagawa-Singer M. Perceptions of diet and physical activity among California Hmong adults and youths. Prev Chronic Dis. 2007;4(4):A93. PubMed ID: 17875268

    • PubMed
    • Search Google Scholar
    • Export Citation
  • 36.

    Culhane-Pera KA, Her C, Her B. “We are out of balance here”: A Hmong cultural model of diabetes. J Immigr Minor Heal. 2007;9(3):179–190. doi:10.1007/s10903-006-9029-3

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 37.

    McMinn AM, van Sluijs EMF, Nightingale CM, et al. Family and home correlates of children’s physical activity in a multi-ethnic population: the cross-sectional Child Heart and Health Study in England (CHASE). Int J Behav Nutr Phys Act. 2011;8:11. PubMed ID: 21324105 doi:10.1186/1479-5868-8-11

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 38.

    Baskin ML, Thind H, Affuso O, Gary LC, LaGory M, Hwang SS. Predictors of moderate-to-vigorous physical activity (MVPA) in African American young adolescents. Ann Behav Med. 2013;45(suppl 1):142–150. doi:10.1007/s12160-012-9437-7

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 2935 665 17
Full Text Views 80 3 0
PDF Downloads 58 5 0